Functional Pathways Research Articles

Exposure to greenspaces sourced soils improves mice gut microbiota

Greenspaces are important components of our living environment and have been linked to various human health. However, the mechanisms underlying the linkages remain unclear. Enriching microbiota has emerged as a novel mechanism, but the corresponding evidence is still limited. We collected soil samples from forest land, grassland, and barren land in Zunyi City, southwestern China and prepared soil solutions. A total of 40 BALB/c mice were evenly divided into normal control group, model control group, forest soil group, grassland soil group, and barren land soil group. After establishing the pseudo germ-free mouse model, different soil solutions were administered through gavage, lasting for seven weeks. Fecal samples were collected and a 16S rRNA high-throughput sequencing analysis was performed. Then, alpha- and beta-diversity were calculated and employed to estimate the effects of soil exposures on mice gut microbial diversity and composition. Further, Linear Discriminant Analysis Effect Size (LEfSe) analysis was carried out to evaluate the effects of soil exposures on gut microbiota specific genera abundances and functional pathways. Compared to mice exposed to barren land soils, those exposed to soils sourced from forest land showed an increase of 0.43 and 70.63 units in the Shannon index and the Observed ASVs, respectively. In addition, exposure to soils sourced from forest land and grassland resulted in healthier changes (i.e., more short-chain fatty acids (SCFAs)-producing bacteria) in gut microbiota than those from barren land. Furthermore, mice exposed to forest soil and grassland soil showed enrichment in 5 and 3 pathways (e.g., butanoate metabolism) compared to those exposed to barren land soil, respectively. In conclusion, exposure to various greenspaces soils may modify the gut microbial communities of mice, potentially fostering a more beneficial microbiota profile. Further research is needed to explore the metabolites of these gut microbiota changes and their correlations with human health.

Identification and validation of autophagy‑related genes in hypertrophic cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is an autosomal dominant cardiac disorder characterized by ventricular hypertrophy resulting from the disordered arrangement of myocardial cells, which leads to impaired cardiac function or death. Autophagy (AT) is a biochemical process through which lysosomes degrade and recycle damaged or discarded intracellular components to protect cells against external environmental conditions, such as hypoxia and oxidative stress. AT is closely related to HCM, and thus, serves an important role in myocardial hypertrophy. However, the precise mechanism underlying the regulation of AT in cardiac hypertrophy remains elusive. The present study aimed to examine the role and mechanisms of AT-related genes (ARGs) in HCM through bioinformatics analysis and experimental validation and to identify potential targeted drugs for HCM. In this study, cardiac samples were obtained from healthy individuals and patients with HCM from the GEO database, and screened for differentially expressed ARGs to further investigate their potential interactions and functional pathways. These genes were subjected to functional enrichment analysis to identify potential crosstalk and involved pathways. Based on a protein-protein interaction network, EIF4EBP1, MCL1, PIK3R1, CCND1 and PPARG were identified as potential biomarkers for the diagnosis and treatment of HCM. Furthermore, 10 components with therapeutic potential for HCM were predicted based on the aforementioned hub genes. The results of bioinformatics analysis were validated using H9c2 cells stimulated with angiotensin II, which represented an in vitro model of cardiac hypertrophy. Overall, the present study demonstrated that the expression levels of ARGs were substantially altered in HCM. Therefore, these genes may be used as diagnostic biomarkers and therapeutic targets for HCM.

Mechanism of Polygala-Acorus in Treating Autism Spectrum Disorder Based on Network Pharmacology and Molecular Docking.

Recent epidemic survey data have revealed a globally increasing prevalence of autism spectrum disorders (ASDs). Currently, while Western medicine mostly uses a combination of comprehensive intervention and rehabilitative treatment, patient outcomes remain unsatisfactory. Polygala-Acorus, used as a pair drug, positively affects the brain and kidneys, and can improve intelligence, wisdom, and awareness; however, the underlying mechanism of action is unclear. We performed network pharmacology analysis of the mechanism of Polygala-Acorus in treating ASD and its potential therapeutic effects to provide a scientific basis for the pharmaceutical's clinical application. The chemical compositions and targets corresponding to Polygala-Acorus were obtained using the Traditional Chinese Medicine Systematic Pharmacology Database and Analysis Platform, Chemical Source Website, and PharmMapper database. Disease targets in ASD were screened using the DisGeNET, DrugBank, and GeneCards databases. Gene Ontology functional analysis and metabolic pathway analysis (Kyoto Encyclopedia of Genes and Genomes) were performed using the Metascape database and validated via molecular docking using AutoDock Vina and PyMOL software. Molecular docking analysis showed that the key active components of Polygala- Acorus interacted with the following key targets: EGFR, SRC, MAPK1, and ALB. Thus, the key active components of Polygala-Acorus (sibiricaxanthone A, sibiricaxanthone B tenuifolin, polygalic acid, cycloartenol, and 8-isopentenyl-kaempferol) have been found to bind to EGFR, SRC, MAPK1, and ALB. This study has preliminarily revealed the active ingredients and underlying mechanism of Polygala-Acorus in the treatment of ASD, and our predictions need to be proven by further experimentation.

Stachyose ameliorates myocardial ischemia–reperfusion injury by inhibiting cardiomyocyte ferroptosis and macrophage pyroptosis

Myocardial ischemia–reperfusion injury (MIRI) is a complex pathological process that results from the restoration of blood flow to ischemic myocardium, leading to a series of detrimental effects including oxidative stress and inflammation. Stachyose, a naturally occurring oligosaccharide found in traditional Chinese medicinal herbs, has been suggested to possess therapeutic properties against various pathological conditions. However, its impact on MIRI and the underlying mechanisms have not been fully elucidated. In this study, we aimed to investigate the therapeutic effects of stachyose on MIRI and to uncover the molecular mechanisms involved. Using both in vivo and in vitro models of MIRI, we evaluated the effects of stachyose on cardiac function and cell death pathways. Our results indicate that stachyose significantly improves cardiac function and reduces infarct size in MIRI mice. Mechanistically, stachyose modulates the ferroptotic pathway in cardiomyocytes by upregulating the expression of glutathione peroxidase 4 (GPX4) and reducing lipid peroxides and iron levels. Additionally, stachyose inhibits the pyroptotic pathway in macrophages by downregulating the expression of NLRP3, gasdermin D (GSMD-N), and cleaved-caspase-1, leading to decreased levels of proinflammatory cytokines interleukin (IL)-1β and IL-18. This study demonstrates that stachyose exerts a protective effect against MIRI by targeting both ferroptosis and pyroptosis pathways, suggesting its potential as a novel therapeutic agent for the treatment of MIRI. Further research is warranted to explore the detailed mechanisms and therapeutic potential of stachyose in clinical settings.

Targeted Regulation of Osteoblasts and Osteoclasts in Osteosarcoma Patients by CSF3R Receptor Inhibition of Osteolysis Caused by Tumor Inflammation Based on Transcriptional Spectrum Analysis and Drug Library Screening.

Osteosarcoma (OS) is a common primary malignant bone tumor that mainly occurs in children and adolescents. The use of IL-8 inhibitor compounds has been reported in patents, which can be used to treat and/or prevent osteosarcoma, but the pathogenesis of osteosarcoma remains to be investigated. At present, osteoblasts and osteoclasts play an important role in the occurrence and development of OS. However, the relationship between osteoblasts and osteoclasts in the specific participation mechanism and inflammatory response of OS patients has not been further studied. The transcriptome, clinical data, and other data related to OS were downloaded from the GEO database to analyze them with 200 known inflammatory response genes. We set the screening conditions as p < 0.05 and | log2FC| > 0.50, screened the differentially expressed genes (DEGs) related to OS, tested the correlation coefficient between the OS INF gene and clinical risk, and analyzed the survival prognosis. We further enriched and analyzed the DEGs and inflammatory response genes of OS with GO/KEGG to explore the potential biological function and signal pathway mechanism of OS inflammatory response genes. Moreover, the virtual screening of drug sensitivity of OS based on the FDA drug library was also carried out to explore potential therapeutic drugs targeted to regulate OS osteogenesis and osteoclast inflammation, and finally, the molecular dynamics simulation verification of OS core protein and potential drugs was carried out to explore the binding stability and mechanism between potential drugs and core protein. Through differential analysis of GSE39058, GSE36001, GSE87624, and three other data sets closely related to OS osteoblasts and osteoclasts, we found that there was one upregulated gene (CADM1) and one down-regulated gene (PHF15) related to OS. In addition, GSEA enrichment analysis of the DEGs of OS showed that it was mainly involved in the progress of OS through biological functions, such as oxidative photosynthesis, acute junction, and epithelial-mesenchymal transition. The enrichment analysis of OS DEGs revealed that they mainly affect the occurrence and progress of OS by participating in the regulation of the actin skeleton, PI3K Akt signal pathway, complement and coagulation cascade. According to the expression of CSF3R in OS patients, a risk coefficient model and a diagnostic model were established. It was found that the more significant the difference in the CSF3R gene in OS patients, the greater the risk coefficient of disease (p < 0.05). The AUC under the curve of the CSF3R gene was greater than 0.65, which had a good diagnostic significance for OS. The above results showed that the prognosis risk gene CSF3R related to OS inflammation was closely related to the survival status of OS patients. Finally, through the virtual screening of the ZINC drug library and molecular dynamics simulation, it was found that the docking model formed by the core protein CSF3R and the compounds, Leucovorin and Methotrexate, were the most stable, which revealed that the compounds Leucovorin and Methotrexate might play a role in the treatment of OS by combining with the inflammatory response related factor CSF3R of OS. CSF3R participates in the occurrence and development of OS bone destruction by regulating the inflammatory response of osteoblasts and osteoclasts and can affect the survival prognosis of OS patients.

Identification of the Roles of Coagulation-related Signature and its Key Factor RABIF in Hepatoma Cell Malignancy.

Hepatoma is a high morbidity and mortality cancer, and coagulation is a potential oncogenic mechanism for hepatoma development. In this study, we aimed to reveal the role of coagulation in hepatoma. We applied the LASSO to construct a coagulation-related risk score (CRS) and a clinical nomogram with independent validation. The heterogeneity of various aspects, including functional enrichment, SNV, CN, immunocyte infiltration, immune pathways, immune checkpoint, and genomic instability indexes, was evaluated. Besides, the prognostic value of the CRS genes was tested. We selected the critical risky gene related to coagulation from the LASSO coefficients, for which we applied transwell and clone formation assays to confirm its roles in hepatoma cell migration and clone formation ability, respectively. The CRS and the nomogram predicted patients' survival with good accuracy in both two datasets. The high-CRS group was associated with higher cell cycle, DNA repair, TP53 mutation rates, amplification, and lower deletion rates at chromosome 1. For immunocyte infiltration, we noticed increased Treg infiltration and globally upregulated immune checkpoints and genomic instability indexes. Additionally, every single CRS gene affected the patient's survival. Finally, we observed that RABIF was the riskiest gene in the CRS. Its knockdown suppressed hepatoma cell migration and clone formation capability, which could be rescued by RABIF overexpression. We built a robust CRS with great potential as a prognosis and immunotherapeutic indicator. Importantly, we identified RABIF as an oncogene, promoting hepatoma cell migration and clone formation, revealing underlying pathological mechanisms, and providing novel therapeutic targets for hepatoma treatment.

Mitochondrial HKDC1 suppresses oxidative stress and apoptosis by regulating mitochondrial function in goose fatty liver

Different from human non-alcoholic fatty liver disease (NAFLD), goose fatty liver is physiological with no inflammation. Consistently, mitochondrial dysfunction, oxidative stress and apoptosis are rarely seen in goose fatty liver. Hexokinase domain-containing protein 1 (HKDC1) is involved in maintaining systemic glucose homeostasis, and its absence causes mitochondrial dysfunction. Here, we demonstrated that mitochondrial outer membrane-bound HKDC1 (mHKDC1) had an expression pattern different from that of whole-cell HKDC1 (wHKDC1). Data indicated that the protein level of whole-cell HKDC1 (wHKDC1) was increased but mHKDC1 was decreased in mouse fatty liver. Interestingly, both the protein levels of wHKDC1 and mHKDC1 were significantly increased in goose fatty liver. Treatment of goose or mouse hepatocytes with fatty liver-related factors could influence the expression of wHKDC1 and mHKDC1, but the influence on wHKDC1 was not identical to mHKDC1. HKDC1 overexpression in goose hepatocytes increased wHKDC1 and mHKDC1 expression, mitochondrial membrane potential (MMP), mitochondrial respiratory chain activity, and suppressed reactive oxygen species (ROS) generation, apoptosis and cytokine-cytokine receptor signaling pathway. In addition, mutations in mitochondrial signal peptide or activation domain of HKDC1 altered MMP or ROS levels. In conclusion, HKDC1, particularly mHKDC1, may protect goose fatty liver by regulating mitochondrial function, ROS generation, apoptosis, and inflammation-related pathways.

Exploring a novel four-gene system as a diagnostic and prognostic biomarker for triple-negative breast cancer, using clinical variables

Triple-negative breast cancer (TNBC) is a subtype of breast cancer with a poor prognosis. This research aims to find real hub genes for prognostic biomarkers of TNBC therapy. The GEO datasets GSE27447 and GSE233242 were analyzed using R package limma to explore DEGs. The PPI was generated using the STRING database. Cytoscape software plug-ins were used to screen the hub genes. Using the DAVID database, GO functional enrichment and KEGG pathway enrichment analysis were performed. Different online expression databases were employed to investigate the functions of real hub genes in tumor driving, diagnosis, and prognosis in TNBC patients with various clinicopathologic characteristics. A total of one hundred DEGs were identified between both datasets. The seven hub genes were identified after the topological parameter analysis of the PPI network. The KEGG pathway and GO analysis suggest that four genes (PSMB1, PSMC1, PSMF1, and PSMD8) are highly enriched in proteasome and were finally considered as real hub genes. Additionally, the expression analysis demonstrated that hub genes were notably up-regulated in TNBC patients compared to controls. Furthermore, correlational analyses revealed the positive and negative correlations among the expression of the real hub genes and various ancillary data, including tumor purity, promoter methylation status, overall survival (OS), genetic alterations, infiltration of CD8+ T and CD4+ immune cells, and a few more, across TNBC samples. Finally, our analysis identified a couple of significant chemotherapeutic drugs, miRNAs and transcription factors (TFS) with intriguing curative potential. In conclusion, we identified four real hub genes as novel biomarkers to overcome heterogenetic-particular challenges in diagnosis, prognosis, and therapy for TNBC patients.

Characteristic alterations of gut microbiota and serum metabolites in patients with chronic tinnitus: a multi-omics analysis

ABSTRACT Chronic tinnitus is a central nervous system disorder. Currently, the effects of gut microbiota on tinnitus remain unexplored. To explore the connection between gut microbiota and tinnitus, we conducted 16S rRNA sequencing of fecal microbiota and serum metabolomic analysis in a cohort of 70 patients with tinnitus and 30 healthy volunteers. We used the weighted gene co-expression network method to analyze the relationship between the gut microbiota and the serum metabolites. The random forest technique was utilized to select metabolites and gut taxa to construct predictive models. A pronounced gut dysbiosis in the tinnitus group, characterized by reduced bacterial diversity, an increased Firmicutes/Bacteroidetes ratio, and some opportunistic bacteria including Aeromonas and Acinetobacter were enriched. In contrast, some beneficial gut probiotics decreased, including Lactobacillales and Lactobacillaceae. In serum metabolomic analysis, serum metabolic disturbances in tinnitus patients and these differential metabolites were enriched in pathways of neuroinflammation, neurotransmitter activity, and synaptic function. The predictive models exhibited great diagnostic performance, achieving 0.94 (95% CI: 0.85–0.98) and 0.96 (95% CI: 0.86–0.99) in the test set. Our study suggests that changes in gut microbiota could potentially influence the occurrence and chronicity of tinnitus, and exert regulatory effects through changes in serum metabolites. Overall, this research provides new perceptions into the potential role of gut microbiota and serum metabolite in the pathogenesis of tinnitus, and proposes the “gut-brain-ear” concept as a pathomechanism underlying tinnitus, with significant clinical diagnostic implications and therapeutic potential. IMPORTANCE Tinnitus affects millions of people worldwide. Severe cases may lead to sleep disorders, anxiety, and depression, subsequently impacting patients’ lives and increasing societal healthcare expenditures. However, tinnitus mechanisms are poorly understood, and effective therapeutic interventions are currently lacking. We discovered the gut microbiota and serum metabolomics changes in patients with tinnitus, and provided the potential pathological mechanisms of dysregulated gut flora in chronic tinnitus. We proposed the innovative concept of the “gut-brain-ear axis,” which underscores the exploration of gut microbiota impact on susceptibility to chronic tinnitus through serum metabolic profile modulation. We also reveal novel biomarkers associated with chronic tinnitus, offering a new conceptual framework for further investigations into the susceptibility of patients, potential treatment targets for tinnitus, and assessing patient prognosis. Subsequently, gut microbiota and serum metabolites can be used as molecular markers to assess the susceptibility and prognosis of tinnitus.Furthermore, fecal transplantation may be used to treat tinnitus.

NMI, POLR3G and APIP are the key molecules connecting glaucoma with high intraocular pressure: a clue for early diagnostic biomarker candidates

AIM: To understand the molecular connectivity between the intraocular pressure (IOP) and glaucoma which will provide possible clues for biomarker candidates. METHODS: The current study uncovers the important genes connecting IOP with the core functional modules of glaucoma. An integrated analysis was performed using glaucoma and IOP microarray datasets to screen for differentially expressed genes (DEGs) in both conditions. To the selected DEGs, the protein interaction network was constructed and dissected to determine the core functional clusters of glaucoma. For the clusters, the connectivity of IOP DEGs was determined. Further, enrichment analyses were performed to assess the functional annotation and potential pathways of the crucial clusters. RESULTS: The gene expression analysis of glaucoma and IOP with normal control showed that 408 DEGs (277 glaucoma and 131 IOP genes) were discovered from two GEO datasets. The 290 DEGs of glaucoma were extended to form a network containing 1495 proteins with 9462 edges. Using ClusterONE, the network was dissected to have 12 clusters. Among them, three clusters were linked with three IOP DEGs [N-Myc and STAT Interactor (NMI), POLR3G (RNA Polymerase III Subunit G), and APAF1-interacting protein (APIP)]. In the clusters, ontology analysis revealed that RNA processing and transport, p53 class mediators resulting in cell cycle arrest, cellular response to cytokine stimulus, regulation of phosphorylation, regulation of type I interferon production, DNA deamination, and cellular response to hypoxia were significantly enriched to be implicated in the development of glaucoma. Finally, NMI, POLR3G, and APIP may have roles that were noticed altered in glaucoma and IOP conditions. CONCLUSION: Our findings could help to discover new potential biomarkers, elucidate the underlying pathophysiology, and identify new therapeutic targets for glaucoma.

Cultivar-dependent differences in plant bud microbiome and functional gene pathways in woody plants commonly used in urban green space.

Plant richness and microbiota have been associated with plant health; hardly any studies have investigated how plant taxa differs in microbiota in the context of human health. We investigated the microbial differences in buds of 83 woody plant taxa used in urban green spaces in hemiboreal climate, using 16S rRNA and whole metagenome shotgun sequencing. Bud microbial community was the richest in Cotoneaster Nanshan and C. integerrimus, and Malus domestica cultivars 'Sandra' and 'Lobo' and poorest in Ribes glandulosum. Metagenomic shotgun sequencing of two M. domestica and four Ribes varieties confirmed differences in taxa in bud microbiota and indicated higher siderophore synthesis in Malus. Microbial richness, including bacteria, archaea and viruses, and functional richness of gene pathways was higher in Malus compared to Ribes. The ten most abundant amplicon sequence units, often referred as species, belonged to the phylum Proteobacteria. The differences between plant taxa were evident in classes Alpha- and Gammaproteobacteria, known for potential human health-benefits. Since environmental microbiota contributes to human microbiota and immunoregulation, horticultural cultivars hosting rich microbiota may have human health benefits. Further studies are needed to confirm the effectiveness of microbially-oriented plant selection in optimizing human microbiota and planetary health.

Mining contextually meaningful subgraphs from a vertex-attributed graph.

Networks have emerged as a natural data structure to represent relations among entities. Proteins interact to carry out cellular functions and protein-Protein interaction network analysis has been employed for understanding the cellular machinery. Advances in genomics technologies enabled the collection of large data that annotate proteins in interaction networks. Integrative analysis of interaction networks with gene expression and annotations enables the discovery of context-specific complexes and improves the identification of functional modules and pathways. Extracting subnetworks whose vertices are connected and have high attribute similarity have applications in diverse domains. We present an enumeration approach for mining sets of connected and cohesive subgraphs, where vertices in the subgraphs have similar attribute profile. Due to the large number of cohesive connected subgraphs and to overcome the overlap among these subgraphs, we propose an algorithm for enumerating a set of representative subgraphs, the set of all closed subgraphs. We propose pruning strategies for efficiently enumerating the search tree without missing any pattern or reporting duplicate subgraphs. On a real protein-protein interaction network with attributes representing the dysregulation profile of genes in multiple cancers, we mine closed cohesive connected subnetworks and show their biological significance. Moreover, we conduct a runtime comparison with existing algorithms to show the efficiency of our proposed algorithm.

Identification and validation of biomarkers related to mitochondria during ex vivo lung perfusion for lung transplants based on machine learning algorithm.

Ex vivo lung perfusion (EVLP) is a critical strategy to rehabilitate marginal donor lungs, thereby increasing lung transplantation (LTx) rates. Ischemia-reperfusion (I/R) injury inevitably occurs during LTx. Exploring the common mechanisms between EVLP and I/R may unveil new treatment targets to enhance LTx outcomes. We obtained datasets from the public Gene Expression Omnibus (GEO) for EVLP (GSE127055 and GSE127057) and I/R (GSE145989) processes. We performed analysis of differential gene expression (DEGs) and Gene Set Enrichment Analysis (GSEA). Mitochondrial genes were sourced from the MitoCarta 3.0 database. Hub mitochondrial-related DEGs (MitoDEGs) were identified using a combination of protein-protein interaction networks and machine learning methods, which were further validated in cell and mice models of EVLP. GSEA analysis of DEGs following EVLP and I/R revealed significant inhibition of mitochondrial function pathways, encompassing mitochondrial central dogma, mtRNA metabolism, OXPHOS assembly factors, metals and cofactors, and heme synthesis and processing processes. Machine learning algorithms including random forest, LASSO, and XGBoost identified five downregulated genes (MTERF1, ACACA, COX15, OSGEPL1, and COQ9) as hub MitoDEGs for both EVLP and I/R processes. We confirmed the reduced expression of these hub MitoDEGs in endothelial cells during EVLP and observed mitochondrial damage in endothelial cells characterized by swollen morphology and cristae disappearance. Imbalance in mitochondrial homeostasis is a shared pathological process during EVLP and I/R-induced lung injury. The identified hub mitochondrial-related genes (MTERF1, ACACA, COX15, OSGEPL1, and COQ9) suggest promising therapeutic targets for lung injury during LTx. The downregulation of these genes indicates a significant disruption in mitochondrial function. This study provides potential mitochondrial-related therapeutic targets for I/R-induced lung injury and for donor lung repair during EVLP procedure in LTx.

Comparative transcriptomic and proteomic analyses of two salt-tolerant alfalfa (Medicago sativa L.) genotypes: investigation of the mechanisms underlying tolerance to salt

Abiotic stressors such as salt stress restrict plant development and output, which lowers agricultural profitability. In this study, alfalfa (Medicago sativa L.) varieties with different levels of salt tolerance were examined using high-throughput RNA sequencing (RNA-Seq) and Tandem Mass Tags (TMT) technologies to study the reactions of the root systems to salt stress, from transcriptomics and proteomics perspectives. The varieties Atlantic (AT) and Zhongmu-1 (ZM-1) were selected and evaluated after 2 h and 6 h of treatment with 150 mM NaCl. The results showed that under salt stress for 2 h, 1810 differentially expressed genes (DEGs) and 160 differentially expressed proteins (DEPs) in AT were screened, while 9341 DEGs and 193 DEPs were screened in ZM-1. Under salt stress for 6 h, 7536 DEGs and 118 DEPs were screened in AT, while 11,754 DEGs and 190 DEPs were screened in ZM-1. Functional annotation and pathway enrichment analyses indicated that the DEGS and DEPs were mainly involved in the glutathione metabolism, biosynthesis of secondary metabolites, glycolysis/gluconeogenesis, carbon fixation in photosynthetic organisms, and photosynthesis pathways. A series of genes related to salt tolerance were also identified, including GSTL3 and GSTU3 of the GST gene family, PER5 and PER10, of the PER gene family, and proteins such as APR and COMT, which are involved in biosynthesis of secondary metabolites. This study provides insights into salt resistance mechanisms in plants, and the related genes and metabolic pathways identified may be helpful for alfalfa breeding in the future.

Subacute Combined Degeneration of the Spinal Cord Caused by an Impairment in the Functional Vitamin B12 Metabolic Pathway

Subacute Combined Degeneration of the Spinal Cord Caused by an Impairment in the Functional Vitamin B12 Metabolic Pathway

Comprehensive analysis of molecular mechanisms underlying kidney stones: gene expression profiles and potential diagnostic markers

BackgroundThe study aimed to investigate the molecular mechanisms underlying kidney stones by analyzing gene expression profiles. They focused on identifying differentially expressed genes (DEGs), performing gene set enrichment analysis (GSEA), weighted gene co-expression network analysis (WGCNA), functional enrichment analysis, and screening optimal feature genes using various machine learning algorithms.MethodsData from the GSE73680 dataset, comprising normal renal papillary tissues and Randall’s Plaque (RP) tissues, were downloaded from the GEO database. DEGs were identified using the limma R package, followed by GSEA and WGCNA to explore functional modules. Functional enrichment analysis was conducted using KEGG and Disease Ontology. Various machine learning algorithms were used for screening the most suitable feature genes, which were then assessed for their expression and diagnostic significance through Wilcoxon rank-sum tests and ROC curves. GSEA and correlation analysis were performed on optimal feature genes, and immune cell infiltration was assessed using the CIBERSORT algorithm.Results412 DEGs were identified, with 194 downregulated and 218 upregulated genes in kidney stone samples. GSEA revealed enriched pathways related to metabolic processes, immune response, and disease states. WGCNA identified modules correlated with kidney stones, particularly the yellow module. Functional enrichment analysis highlighted pathways involved in metabolism, immune response, and disease pathology. Through machine learning algorithms, KLK1 and MMP10 were identified as optimal feature genes, significantly upregulated in kidney stone samples, with high diagnostic value. GSEA further elucidated their biological functions and pathway associations.ConclusionThe study comprehensively analyzed gene expression profiles to uncover molecular mechanisms underlying kidney stones. KLK1 and MMP10 were identified as potential diagnostic markers and key players in kidney stone progression. Functional enrichment analysis provided insights into their roles in metabolic processes, immune response, and disease pathology. These results contribute significantly to a better understanding of kidney stone pathogenesis and may inform future diagnostic and therapeutic strategies.

Utilizing Artificial Intelligence for Microbiome Decision-Making: Autism Spectrum Disorder in Children from Bosnia and Herzegovina

Background/Objectives: The study of microbiome composition shows positive indications for application in the diagnosis and treatment of many conditions and diseases. One such condition is autism spectrum disorder (ASD). We aimed to analyze gut microbiome samples from children in Bosnia and Herzegovina to identify microbial differences between neurotypical children and those with ASD. Additionally, we developed machine learning classifiers to differentiate between the two groups using microbial abundance and predicted functional pathways. Methods: A total of 60 gut microbiome samples (16S rRNA sequences) were analyzed, with 44 from children with ASD and 16 from neurotypical children. Four machine learning algorithms (Random Forest, Support Vector Classification, Gradient Boosting, and Extremely Randomized Tree Classifier) were applied to create eight classification models based on bacterial abundance at the genus level and KEGG pathways. Model accuracy was evaluated, and an external dataset was introduced to test model generalizability. Results: The highest classification accuracy (80%) was achieved with Random Forest and Extremely Randomized Tree Classifier using genus-level taxa. The Random Forest model also performed well (78%) with KEGG pathways. When tested on an independent dataset, the model maintained high accuracy (79%), confirming its generalizability. Conclusions: This study identified significant microbial differences between neurotypical children and children with ASD. Machine learning classifiers, particularly Random Forest and Extremely Randomized Tree Classifier, achieved strong accuracy. Validation with external data demonstrated that the models could generalize across different datasets, highlighting their potential use.

Abstract PR004: Biological insights into tissue-agnostic plasma cfDNA methylation signature for surveillance of head and neck tumor recurrence

Abstract BACKGROUND: We recently described a clinical validation of a tissue-agnostic genome-wide methylome enrichment molecular residual disease (MRD) assay for head and neck cancers (HNC) (Liu, ESMO 2024). Herein, we investigate the cfDNA methylation signature utilized by this test to demonstrate the biological relevance with respect to the tissue of origin and epigenetic mechanisms of dysregulation that alter normal cellular activity. We evaluate the signature to gain insights and to characterize the biology of this biomarker and to investigate the application of cfMeDIP-seq assay as a diagnostic tool. METHODS: From unblinded training set of 163 HNC patients, including HPV+ (n = 76), HPV- (n = 43), and HPV-unknown (n = 44) individuals, a cfDNA methylation classifier signature was developed to detect recurrence (n MRD+ = 62, n MRD- = 101) in samples from blood draws approximately at 3, 12, and 24 months post curative intent treatment using cfMeDIP-seq assay. Clinical performance of the signature was then successfully validated in a blinded HNC validation cohort (n = 162), including HPV+ and HPV- patients (Liu, ESMO 2024). Here, the signature’s ability to detect ctDNA was assessed using HNC tumor tissue (n = 523), adjacent normal tissue (n = 45), and healthy peripheral blood leukocytes (n = 93) DNA methylation data from TCGA. The signature’s ability to provide biological insights was assessed by evaluating enrichment in CpG elements, epigenetic regulators, regulatory pathways, and other biological pathways. RESULTS: Identified differentially methylated regions (DMRs) were significantly hypermethylated in HNC tumor tissue samples when compared to adjacent normal and healthy peripheral blood leukocytes (P = 1.3e-131), and the mean signature signal within tumor tissue samples correlated with tumor purity (P = 2.47e-21). These DMRs were also significantly enriched in CpG islands, shores, and shelves and could classify HNC patients into identifiable molecular subtypes. Further analysis of the DMRs, based on their genomic coordinates, shows association with known cancer genes and significant enrichment in pathways known to be associated with HNC, for example, epithelial to mesenchymal transition (P = 1.76e-4), and multiple functional pathways involved in DNA and transcription factor binding, transcriptional regulation, and chromatin remodeling. CONCLUSIONS: These results, along with the previous clinical validation, provide strong evidence that the cfDNA methylation signature developed in HNC detects ctDNA shed from residual tumor and provide insights into relevant tumor biology and epigenetic mechanisms, including CpG island hypermethylation and epithelial to mesenchymal transition. Furthermore, these data support the generalization of biomarker detection utilizing cfMeDIP-seq to a broad spectrum of indications. Citation Format: Yulia Newton, Justin Burgener, Margaret Gruca, Collin Melton, Jun Min, Abel Licon, Scott Bratman, Alan Williams, Daniel D De Carvalho. Biological insights into tissue-agnostic plasma cfDNA methylation signature for surveillance of head and neck tumor recurrence [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr PR004.

Macrophage-Specific Lactate Dehydrogenase Expression Modulates Inflammatory Function In Vitro.

In acute kidney injury, macrophages play a major role in regulating inflammation. Classically activated macrophages (M1) undergo drastic metabolic reprogramming during their differentiation and upregulate the aerobic glycolysis pathway to fulfill their pro-inflammatory functions. NAD+ regeneration is crucial for the maintenance of glycolysis and the most direct pathway by which this occurs is via the fermentation of pyruvate to lactate, catalyzed by lactate dehydrogenase A (LDHA). Our previous study determined that LDHA is predominantly expressed in the proximal segments of the nephron in the mouse kidney and increases with hypoxia. This study investigates the potential of LDHA as a therapeutic target for inflammation by exploring its role in macrophage function in vitro. Bone-marrow-derived macrophages (BMDMs) were isolated from myeloid-specific LDHA knockout mice derived from crossbreeding LysM-Cre transgenic mice and LDHA floxed mice. RNA sequencing and LC-MS/MS metabolomics analyses were used in this study to determine the effect of LDHA deletion on BMDM following stimulation with IFN-γ. LDHA deletion in IFN-γ BMDMs resulted in a significant alteration of the macrophage activation and functional pathways, and change in glycolytic, cytokine, and chemokine gene expression. Metabolite concentrations associated with pro-inflammatory macrophage profiles were diminished while anti-inflammatory-associated ones were increased in LDHA KO BMDMs. Glutamate and amino sugars metabolic pathways were significantly affected by the LDHA deletion. A combined muti-omics analysis highlighted changes in Rap1 signaling, cytokine-cytokine receptor interaction, focal adhesion, and MAPK signaling metabolism pathways. Deletion of LDHA in macrophages results in a notable reduction in the pro-inflammatory profile and concurrent upregulation of anti-inflammatory pathways. These findings suggest that LDHA could serve as a promising therapeutic target for inflammation, a key contributor to the pathogenesis of acute kidney injury.

Renoprotective Effects of Brown-Strain Flammulina velutipes Singer in Chronic Kidney Disease-Induced Mice Through Modulation of Oxidative Stress and Inflammation and Regulation of Renal Transporters

Cisplatin, widely used in chemotherapy, acts through mechanisms such as oxidative stress to damage the DNA and cause the apoptosis of cancer cells. Although effective, cisplatin treatment is associated with considerable side effects including chronic kidney disease (CKD). Studies on brown-strain Flammulina velutipes Singer (FVB) have shown its significant antioxidant and immunomodulatory effects. High-performance liquid chromatography (HPLC) confirmed that the FVB extract contained gallic acid and quercetin. This study investigated whether FVB extract can improve and protect against cisplatin-induced CKD in mice. C57BL/6 mice were used as an animal model, and CKD was induced through intraperitoneal cisplatin injection. FVB was orally administered to the mice for 14 consecutive days. N-acetylcysteine (NAC) was administered in the positive control group. Organ pathology and serum biochemical analyses were conducted after the mice were sacrificed. Significant dose-dependent differences were discovered in body mass, kidney mass, histopathology, renal function, inflammatory factors, and antioxidant functions among the different groups. FVB extract reduced the severity of cisplatin-induced CKD in pathways related to inflammation, autophagy, apoptosis, fibrosis, oxidative stress, and organic ion transport proteins; FVB extract, thus, displays protective physiological activity in kidney cells. Additionally, orally administered high doses of the FVB extract resulted in significantly superior renal function, inflammatory factors, antioxidative activity, and fibrotic pathways. This study establishes a strategy for future clinical adjunctive therapy using edible-mushroom-derived FVB extract to protect kidney function.